Sequence Braiding: Visual overviews of temporal event sequences and attributes

The visualization produced by Sequence Braiding - a visualization of the sequences of meals in several days of a person with type 1 diabetes. Every meal is color coded according to the blood glucose level of the patient at the time of the meal, and meals with the same blood glucose are grouped together. Edges connect subsequent meals. This produces a visualization in which trends or outliers stand out.
An example of SEQUENCE BRAIDING applied to blood glucose and meal data of a patient with type 1 diabetes. This temporal event sequence and attribute data is modeled using a layered directed acyclic network, where each node represents an individual event (meal) and contiguous edges connect the events from a single day in sequence. Nodes are aligned into columns based on their event (meal) type and into rows based on attribute values, in this case quantitative blood glucose groups. Nodes are also color-coded by attribute group

Temporal event sequence alignment has been used in many domains to visualize nuanced changes and interactions over time. Existing approaches align one or two sentinel events. Overview tasks require examining all alignments of interest using interaction and time or juxtaposition of many visualizations. Furthermore, any event attribute overviews are not closely tied to sequence visualizations. We present SEQUENCE BRAIDING, a novel overview visualization for temporal event sequences and attributes using a layered directed acyclic network. SEQUENCE BRAIDING visually aligns many temporal events and attribute groups simultaneously and supports arbitrary ordering, absence, and duplication of events. In a controlled experiment we compare SEQUENCE BRAIDING and IDMVis on user task completion time, correctness, error, and confidence. Our results provide good evidence that users of SEQUENCE BRAIDING can understand high-level patterns and trends faster and with similar error. A full version of this paper with all appendices; the evaluation stimuli, data, and analysis code; and source code are available at

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